Machine Learning courses

1770 Courses

Udemy

RPA Skill Course for CA's and Finance professionals

Elevate your finance expertise with our intensive RPA Skill Course crafted explicitly for Chartered Accountants and finance professionals. This course is meticulously structured to cover over 28 important topics, ensuring a robust understanding of RPA technology concepts applied in the finance industry. Offered through Udemy, this course prov.

Coursera

Oracle Cloud Infrastructure Generative AI Professional

Enhance your expertise in cloud-based artificial intelligence by enrolling in the Oracle Cloud Infrastructure Generative AI Professional course. This course is designed to provide you with a deep understanding of Large Language Models (LLMs) and guide you through mastering the OCI Generative AI Service. You will also learn to build an innovat.

Udemy

Machine Learning for Data Analysis: Regression & Forecasting

Unlock the power of machine learning for data analysis with our comprehensive course. Designed to make machine learning simple, this course focuses on using Excel for advanced regression models and business intelligence applications, so you can dive deep into data without the need for any coding experience. Whether you're interested in Mach.

Johns Hopkins University

Advanced Neural Network Techniques

Join the 'Advanced Neural Network Techniques' course and delve into the world of sophisticated neural network methodologies. This comprehensive program provides learners with an in-depth understanding of cutting-edge techniques like Recurrent Neural Networks (RNNs), Autoencoders, Generative Neural Networks, and Deep Reinforcement Learning. Offe.

Udemy

PyTorch Tutorial - Neural Networks & Deep Learning in Python

Udemy

SAP Analytics Cloud - Master Class

Step up your skills with the SAP Analytics Cloud Master Class and transform yourself into the SAC expert your business needs. Gain valuable insights and learn real-world tips & tricks from an experienced dashboard practitioner. Offered by Udemy, this comprehensive course spans multiple categories to sharpen your expertise, including: Mac.

Udemy

Quantum Computing and Quantum Machine Learning - Part 2

Explore the fascinating realms of quantum computing and quantum machine learning in Part 2 of this comprehensive course. Gain a robust understanding of quantum principles and learn to navigate the intricate world of quantum gates and programming. Offered by Udemy, this course is ideal for enthusiasts of Artificial Intelligence, Python, and Qua.

Coursera

AI Security

Discover the intricate world of AI with our AI Security course, perfect for those in technical roles seeking legal insights or legal experts exploring the technicalities of AI. Offered by Coursera, this course provides an in-depth understanding of AI's diverse applications and the contexts in which it will likely be utilized. Dive into compre.

Coursera

Oracle Cloud Infrastructure AI Foundations

Join the Oracle Cloud Infrastructure AI Foundations course and dive into the world of AI. This course offers an in-depth introduction to key concepts in Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI. Specifically designed for those new to the field, it emphasizes practical applications of these technologies withi.

Udemy

Introduction to AI Governance

Dive into the critical aspects of AI governance with our comprehensive course on Udemy. Learn effective strategies to measure, monitor, and control your AI models, ensuring they function within desired parameters and ethical standards. Whether you're an AI enthusiast looking to deepen your knowledge or a professional seeking to understand AI.

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Machine learning use cases

The use of machine learning has touched many areas in our lives. Let's look at the most striking examples of the use of computer intelligence:

Voice assistant Alisa. This system, without human help, will always find the answer to any question of interest, turn on music, answer the call and much more.

Selecting relevant advertising in browsers is not an easy process for a person, but it is quick for a computer. The system will analyze the viewing data and select what a particular user will like. The same system is used on various marketplaces - products that a person viewed or purchased are offered.

Chatbots in various dialogues. For example, many banks use bots to solve customer problems. It's convenient and fast.

Data security: Machine learning models can identify data security vulnerabilities before they become breaches. By analyzing past experiences, machine learning models can predict future high-risk actions so that risk can be mitigated proactively.

Finance: Banks, trading brokers and fintech firms use machine learning algorithms to automate trading and provide financial advisory services to investors. Bank of America uses chatbot Erica to automate customer support.

Healthcare: Machine learning is used to analyze massive medical data sets to speed up the discovery of treatments and cures, improve patient outcomes, and automate routine processes to prevent human errors. For example, IBM Watson uses data mining to provide doctors with data they can use to personalize patient care.

Fraud detection: AI is used in the finance and banking sector to autonomously analyze large numbers of transactions to identify fraudulent activities in real time. Technology services company Capgemini says fraud detection systems using machine learning and analytics reduce fraud investigation time by 70% and increase detection accuracy by 90% .

Retail: AI researchers and developers are using machine learning algorithms to develop AI recommendation engines that make relevant product suggestions based on shoppers' past choices, as well as historical, geographic and demographic data.

Facial recognition in the subway will help identify violators or criminals in a huge mass of people. Ordinary observers cannot cope with this task. But a fast-learning machine will do this job without any problems.

What do you need for machine learning (ML)?

For those interested in training, there are several requirements to be met in order to be successful in this field. So, there are the main points you need to know about the machine learning course. These requirements include:

Basic knowledge of programming languages such as Python, R, Java, JavaScript, etc.

Average knowledge of statistics and probability.

Basic knowledge of linear algebra in the ml course. In a linear regression model, a line is drawn through all the data points, and that line is used to calculate new values.

Understanding Calculus.

Knowledge of how to clean and structure raw data into the desired format to reduce the time required for decision making.

Machine learning courses from AI Eeducation are the best choice!